[Superseded]

rename_if(), rename_at(), and rename_all() have been superseded by rename_with(). The matching select statements have been superseded by the combination of a select() + rename_with().

These functions were superseded because mutate_if() and friends were superseded by across(). select_if() and rename_if() already use tidy selection so they can't be replaced by across() and instead we need a new function.

select_all(.tbl, .funs = list(), ...)

rename_all(.tbl, .funs = list(), ...)

select_if(.tbl, .predicate, .funs = list(), ...)

rename_if(.tbl, .predicate, .funs = list(), ...)

select_at(.tbl, .vars, .funs = list(), ...)

rename_at(.tbl, .vars, .funs = list(), ...)

Arguments

.tbl

A tbl object.

.funs

A function fun, a purrr style lambda ~ fun(.) or a list of either form.

...

Additional arguments for the function calls in .funs. These are evaluated only once, with tidy dots support.

.predicate

A predicate function to be applied to the columns or a logical vector. The variables for which .predicate is or returns TRUE are selected. This argument is passed to rlang::as_function() and thus supports quosure-style lambda functions and strings representing function names.

.vars

A list of columns generated by vars(), a character vector of column names, a numeric vector of column positions, or NULL.

Examples

mtcars <- as_tibble(mtcars) # for nicer printing mtcars %>% rename_all(toupper)
#> # A tibble: 32 x 11 #> MPG CYL DISP HP DRAT WT QSEC VS AM GEAR CARB #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # … with 22 more rows
# -> mtcars %>% rename_with(toupper)
#> # A tibble: 32 x 11 #> MPG CYL DISP HP DRAT WT QSEC VS AM GEAR CARB #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # … with 22 more rows
# NB: the transformation comes first in rename_with is_whole <- function(x) all(floor(x) == x) mtcars %>% rename_if(is_whole, toupper)
#> # A tibble: 32 x 11 #> mpg CYL disp HP drat wt qsec VS AM GEAR CARB #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # … with 22 more rows
# -> mtcars %>% rename_with(toupper, where(is_whole))
#> # A tibble: 32 x 11 #> mpg CYL disp HP drat wt qsec VS AM GEAR CARB #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # … with 22 more rows
mtcars %>% rename_at(vars(mpg:hp), toupper)
#> # A tibble: 32 x 11 #> MPG CYL DISP HP drat wt qsec vs am gear carb #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # … with 22 more rows
# -> mtcars %>% rename_with(toupper, mpg:hp)
#> # A tibble: 32 x 11 #> MPG CYL DISP HP drat wt qsec vs am gear carb #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # … with 22 more rows
# You now must select() and then rename mtcars %>% select_all(toupper)
#> # A tibble: 32 x 11 #> MPG CYL DISP HP DRAT WT QSEC VS AM GEAR CARB #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # … with 22 more rows
# -> mtcars %>% rename_with(toupper)
#> # A tibble: 32 x 11 #> MPG CYL DISP HP DRAT WT QSEC VS AM GEAR CARB #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # … with 22 more rows
# Selection drops unselected variables: mtcars %>% select_if(is_whole, toupper)
#> # A tibble: 32 x 6 #> CYL HP VS AM GEAR CARB #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 6 110 0 1 4 4 #> 2 6 110 0 1 4 4 #> 3 4 93 1 1 4 1 #> 4 6 110 1 0 3 1 #> 5 8 175 0 0 3 2 #> 6 6 105 1 0 3 1 #> 7 8 245 0 0 3 4 #> 8 4 62 1 0 4 2 #> 9 4 95 1 0 4 2 #> 10 6 123 1 0 4 4 #> # … with 22 more rows
# -> mtcars %>% select(where(is_whole)) %>% rename_with(toupper)
#> # A tibble: 32 x 6 #> CYL HP VS AM GEAR CARB #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 6 110 0 1 4 4 #> 2 6 110 0 1 4 4 #> 3 4 93 1 1 4 1 #> 4 6 110 1 0 3 1 #> 5 8 175 0 0 3 2 #> 6 6 105 1 0 3 1 #> 7 8 245 0 0 3 4 #> 8 4 62 1 0 4 2 #> 9 4 95 1 0 4 2 #> 10 6 123 1 0 4 4 #> # … with 22 more rows
mtcars %>% select_at(vars(-contains("ar"), starts_with("c")), toupper)
#> # A tibble: 32 x 10 #> MPG CYL DISP HP DRAT WT QSEC VS AM CARB #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 #> # … with 22 more rows
# -> mtcars %>% select(!contains("ar") | starts_with("c")) %>% rename_with(toupper)
#> # A tibble: 32 x 10 #> MPG CYL DISP HP DRAT WT QSEC VS AM CARB #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 #> # … with 22 more rows